Unmanned, off-road dump trucks (referred to below as unmanned dump trucks) are widely used in mines to release personnel from arduous labor, lower production costs, and to reduce fuel consumption.
These unmanned dump trucks are equipped with the following so as to automate their motion: a device for measuring travel position using dead reckoning and GPS, a storage device for storing course data, and a control device for controlling the movement of the unmanned dump truck based on the travel position and course data.
A widely used method for preparing course data is a teaching system wherein the unmanned dump truck is actually operated and its travel positions are stored.
The course data are generally prepared with a teaching system for recording the positions of the dump truck over time while the unmanned dump truck is actually operated.
The course data prepared by the teaching system show the conditions of actual vehicle travel. Consequently, the contents thereof include position data satisfying travel speed, acceleration and deceleration and the lateral acceleration, which were actually possible for the vehicle to run under the conditions of the course in that instance. Furthermore, the course data include elements which are difficult to find through automatic calculations, such as the appropriate deceleration for an anticipated curve or acceleration for an anticipated upward grade. Moreover, the teaching system is easy for an operator to understand, since the operator just drives the vehicle.
For these reasons, the procedure for preparing course data with a teaching system is widely used.
Meanwhile, the technique of combining the teaching system with an offline system of preparing the course on a computer, according to the complexity of the course, has also been proposed (Japanese Patent Laid-open No. 8-101712).
In this way, the teaching system handles simple portions, such as straight sections, offline and handles complex portions where interference is likely in the vehicle.
Course data prepared by the teaching show the path actually traveled by the unmanned dump truck.
However, the vehicle in operation may not necessarily travel on the same course that was taught as a result of errors in position measurement or errors in the control of the vehicle using the measured positions.
For this reason, there is a risk that the vehicle, which traveled in the course area during the teaching operation, may travel outside of the course area and have an accident while repeating the actual course.
During teaching, the operator may anticipate the errors when operating the vehicle, but this is certainly not a perfect system. Furthermore, when the vehicle must pass other vehicles or when the area traveled is narrow, it is a difficult job to perform teaching for anticipating errors during travel and for avoiding interference with other vehicles and areas outside the course area.
The present invention was made in view of these circumstances and it is an object of the present invention to provide an interference prediction apparatus for unmanned vehicles which can predict interference of an unmanned vehicle when the vehicle is guided by course data prepared through teaching or the like.